The quasi-particle gap in a disordered boson Hubbard model in two dimensions

We investigate the behavior of the quasi-particle energy gap near quantum phase transitions in a two-dimensional disordered boson Hubbard model at a commensurate filling. Via Monte Carlo simulations of ensembles with fixed numbers of particles, we observe the behavior of the gap as a function of the tuning parameter for various strength of diagonal disorder. For weak disorder, we find that gapped Mott insulating phase is sustained up to the transition point and disappears only in a superfluid, strongly supporting a direct Mott-insulator-to-superfluid transition. Bose glass behavior, insulating with vanishing gap, appears only when the strength of disorder is bigger than a critical value

Click-aware purchase prediction with push at the top

Eliciting user preferences from purchase records for performing purchase prediction is challenging because negative feedback is not explicitly observed, and because treating all non-purchased items equally as negative feedback is unrealistic. Therefore, in this study, we present a framework that leverages the past click records of users to compensate for the missing user-item interactions of purchase records, i.e., non-purchased items. We begin by formulating various model assumptions, each one assuming a different order of user preferences among purchased, clicked-but-not-purchased, and non-clicked items, to study the usefulness of leveraging click records. We implement the model assumptions using the Bayesian personalized ranking model, which maximizes the area under the curve for bipartite ranking. However, we argue that using click records for bipartite ranking needs a meticulously designed model because of the relative unreliableness of click records compared with that of purchase records. Therefore, we ultimately propose a novel learning-to-rank method, called P3Stop, for performing purchase prediction. The proposed model is customized to be robust to relatively unreliable click records by particularly focusing on the accuracy of top-ranked items. Experimental results on two real-world e-commerce datasets demonstrate that P3STop considerably outperforms the state-of-the-art implicit-feedback-based recommendation methods, especially for top-ranked items.Comment: For the final published journal version, see https://doi.org/10.1016/j.ins.2020.02.06

Effect of geopolymer composition and curing conditions on efflorescence in lightweight porous geopolymers

Lightweight geopolymers are more readily produced and give higher fire resistant performance than foam cement concrete. The fly ash-based lightweight geopolymers stones could be used for decoration due to the similarity in appearance and color to natural vesicular basalts. Efflorescence can be even more nettlesome issue in commercialization of lightweight porous geopolimers. Lowering the density of solid geopolymers can be achieved by inducing chemical reactions that entrain gases to foam the geopolymer structure. The apparent density of lightweight porous geopolymers has a range from 0.7 to 1.2 g/m3 with 0.025, 0.05 and 0.10 wt% of Al powder concentration, which corresponds to about 37~60 % of the apparent density, 1.96 g/cm3, of solid geopolymers. The compressive strength of cellular structured geopolymers decreased to 6~18 % of the compressive strength, 45 MPa of solid geopolymers. The microstructure of geopolymers gel was equivalent for both solid and cellular structured geopolymers. The efflorescence can be controlled by reducing targeted Na/Al molar ratio less than 1.0 or water content in geopolymers or curing at high temperature. Please click Additional Files below to see the full abstract

Reynolds Averaged Solutions of the Navier-Stokes Equation

The mean of Young measure solutions for the Navier-Stokes equations with general initial conditions are PDE solutions of the Navier-Stokes equation of the class considered by Leray and Hopf.Comment: arXiv admin note: substantial text overlap with arXiv:2212.1473